Pre-Testing Research Data Collection Instruments

The tool or instrument of data collection namely the schedule or the questionnaire should be pre-tested before adopted for data collection on the study. Pre-testing simply means, testing the validity, reliability, practicability and sensitivity of the tool before it is used for actual data collection. The only way to gain assurance that questions are unambiguous is to try them on a selected small group of prospective respondents.

Process of Pre-testing

Pre-testing can be done in parts. Different sub-parts in the main part of the questionnaire/schedule can be differently pre-tested. So a series of small pre-test on different units of the tool can be done. A full scale pre-test of the whole tool can be done if needed finally or in lieu of the series of pre-tests is small bits.

Pre-testing must be done on a sample that is representatives of the population. May be 10 to 12 respondents for pre-testing are good.

Importance of pre-testing

The following are the objectives of pre-testing of data collection tools:

To detect discrepancies in the tool and rectify the same. This is needed to find where the shoe bites and making amends for the same.

To detect the difficulties encountered by the respondents while filling up the questionnaire / schedule and make remedies for the same.

To detect possible misunderstood, un-understood aspects of the tool and rectify the same.

The sequence of questions is better ordered in the light of feedback received.

To get now insights into the problem based on responses received through pre-test and incorporate them in the tool and thereby enriching the tool.

To take note of flabby parts in the tool and remove them to make the tool slim and fit.

To re-size the tool based on time taken for filling up the questionnaire. The tool is thus right sized.

Goode and Hatt (1952) indicated the following as signs or symptoms of defective schedule / questionnaire which may be seen during pre-testing:

Lack of proper order in the responses,

All are none responses,

Large number of “do not know” or “do not understand” answers,

Many qualified answers or irrelevant opinions,

High proportion of refusals to answer,

High degree of variance in answers when the questions order is changed,